Environmental Costs of Government-Sponsored Agrarian Settlements in Brazilian Amazonia

Brazil has presided over the most comprehensive agrarian reform frontier colonization program on Earth, in which ~1.2 million settlers have been translocated by successive governments since the 1970's, mostly into forested hinterlands of Brazilian Amazonia. These settlements encompass 5.3% of this ~5 million km2 region, but have contributed with 13.5% of all land conversion into agropastoral land uses. The Brazilian Federal Agrarian Agency (INCRA) has repeatedly claimed that deforestation in these areas largely predates the sanctioned arrival of new settlers. Here, we quantify rates of natural vegetation conversion across 1911 agrarian settlements allocated to 568 Amazonian counties and compare fire incidence and deforestation rates before and after the official occupation of settlements by migrant farmers. The timing and spatial distribution of deforestation and fires in our analysis provides irrefutable chronological and spatially explicit evidence of agropastoral conversion both inside and immediately outside agrarian settlements over the last decade. Deforestation rates are strongly related to local human population density and road access to regional markets. Agrarian settlements consistently accelerated rates of deforestation and fires, compared to neighboring areas outside settlements, but within the same counties. Relocated smallholders allocated to forest areas undoubtedly operate as pivotal agents of deforestation, and most of the forest clearance occurs in the aftermath of government-induced migration

Molecular identification of Palearctic members of Anopheles maculipennis in northern Iran

BACKGROUND: Members of Anopheles maculipennis complex are effective malaria vectors in Europe and the Caspian Sea region in northern Iran, where malaria has been re-introduced since 1994. The current study has been designed in order to provide further evidence on the status of species composition and to identify more accurately the members of the maculipennis complex in northern Iran. METHODS: The second internal transcribed spacer of ribosomal DNA (rDNA-ITS2) was sequenced in 28 out of 235 specimens that were collected in the five provinces of East Azerbayjan, Ardebil, Guilan, Mazandaran and Khorassan in Iran. RESULTS: The length of the ITS2 ranged from 283 to 302 bp with a GC content of 49.33 – 54.76%. No intra-specific variations were observed. Construction of phylogenetic tree based on the ITS2 sequence revealed that the six Iranian members of the maculipennis complex could be easily clustered into three groups: the An. atroparvus – Anopheles labranchiae group; the paraphyletic group of An. maculipennis, An. messeae, An. persiensis; and An. sacharovi as the third group. CONCLUSION: Detection of three species of the An. maculipennis complex including An. atroparvus, An. messae and An. labranchiae, as shown as new records in northern Iran, is somehow alarming. A better understanding of the epidemiology of malaria on both sides of the Caspian Sea may be provided by applying the molecular techniques to the correct identification of species complexes, to the detection of Plasmodium composition in Anopheles vectors and to the status of insecticide resistance by looking to related genes

Early prediction of cardiac resynchronization therapy response by non-invasive electrocardiogram markers

[EN] Cardiac resynchronization therapy (CRT) is an effective treatment for those patients with severe heart failure. Regrettably, there are about one third of CRT "non-responders", i.e. patients who have undergone this form of device therapy but do not respond to it, which adversely affects the utility and cost-effectiveness of CRT. In this paper, we assess the ability of a novel surface ECG marker to predict CRT response. We performed a retrospective exploratory study of the ECG previous to CRT implantation in 43 consecutive patients with ischemic (17) or non-ischemic (26) cardiomyopathy. We extracted the QRST complexes (consisting of the QRS complex, the S-T segment, and the T wave) and obtained a measure of their energy by means of spectral analysis. This ECG marker showed statistically significant lower values for non-responder patients and, joint with the duration of QRS complexes (the current gold-standard to predict CRT response), the following performances: 86% accuracy, 88% sensitivity, and 80% specificity. In this manner, the proposed ECG marker may help clinicians to predict positive response to CRT in a non-invasive way, in order to minimize unsuccessful procedures.This work was supported by MINECO under grants MTM2013-43540-P and MTM2016-76647-P.Ortigosa, N.; Pérez-Roselló, V.; Donoso, V.; Osca Asensi, J.; Martínez-Dolz, L.; Fernández Rosell, C.; Galbis Verdu, A. (2018). Early prediction of cardiac resynchronization therapy response by non-invasive electrocardiogram markers. Medical & Biological Engineering & Computing. 56(4):611-621. https://doi.org/10.1007/s11517-017-1711-1S611621564Boggiatto P, Fernández C, Galbis A (2009) A group representation related to the stockwell transform. Indiana University Mathematics Journal 58(5):2277–2296Brignole M, Auricchio A, Baron-Esquivias G, Bordachar P, Boriani G et al (2013) 2013 ESC guidelines on cardiac pacing and cardiac resynchronization therapy. Europace 15:1070–1118Brown RA, Lauzon ML, Frayne R (2010) A general description of linear time-frequency transforms and formulation of a fast, invertible transform that samples the continuous s-transform spectrum nonredundantly. IEEE Trans Signal Process 58(1): 281–290Carità P, Corrado E, Pontone G, Curnis A, Bontempi L et al (2016) Non-responders to cardiac resynchronization therapy: insights from multimodality imaging and electrocardiography. A brief review. Int J Cardiol 225:402–407Cazeau S, Leclercq C, Lavergne T, Walker S, Varma C, Linde C et al (2001) Effects of multisite biventricular pacing in patients with heart failure and intraventricular conduction delay. N Engl J Med 344:873–880Chang CC, Lin CJ (2011) LIBSVM: a library for support vector machines. ACM Trans Intell Syst Technol 2(3):27:1–27:27Chawla NV, Bowyer KW, Hall LO, Kegelmeyer WP (2002) SMOTE: synthetic minority over-sampling technique. J Artif Intell Res 16(1):321–357Cleland JGF, Abraham WT, Linde C, Gold MR, Young J et al (2013) An individual patient meta-analysis of five randomized trials assessing the effects of cardiac resyn- chronization therapy on morbidity and mortality in patients with symptomatic heart failure. Eur Heart Journal 34(46):3547–3556Cleland JGF, Calvert MJ, Verboven Y, Freemantle N (2009) Effects of cardiac resynchronization therapy on long-term quality of life: an analysis from the Cardiac Resynchronisation-Heart Failure (CARE-HF) study. Am Heart J 157:457–466Cleland JGF, Freemantle N, Erdmann E, Gras D, Kappenberger L et al (2012) Long-term mortality with cardiac resynchronization therapy in the Cardiac Resynchronization-Heart Failure (CARE-HF) trial. Eur J Heart Fail 14:628–634Egoavil CA, Ho RT, Greenspon AJ, Pavri BB (2005) Cardiac resynchronization therapy in patients with right bundle branch block: analysis of pooled data from the MIRACLE and Contak CD trials. Heart Rhythm 2(6):611–615Engels EB, Mafi-Rad M, van Stipdonk AM, Vernooy K, Prinzen FW (2016) Why QRS duration should be replaced by better measures of electrical activation to improve patient selection for cardiac resynchronization therapy. J Cardiovasc Transl Res 9(4):257–265Engels EB, Végh EM, Van Deursen CJ, Vernooy K, Singh JP, Prinzen FW (2015) T-wave area predicts response to cardiac resynchronization therapy in patients with left bundle branch block. J Cardiovasc Electrophysiol 26(2):176–183Eschalier R, Ploux S, Ritter P, Haïssaguerre M, Ellenbogen K, Bordachar P (2015) Nonspecific intraventricular conduction delay: definitions, prognosis, and implications for cardiac resynchronization therapy. Heart Rhythm 12(5):1071–1079Goldenberg I, Kutyifa V, Klein HU, Cannom DS, Brown MW et al (2014) Survival with cardiac-resynchronization therapy in mild heart failure. N Engl J Med 370:1694–1701He H, Bai Y, Garcia EA, Li S (2008) ADASYN: adaptive synthetic sampling approach for imbalanced learning. In: International joint conference on neural networks, pp 1322–1328Jacobsson J, Borgguist R, Reitan C, Ghafoori E, Chatterjee NA et al (2016) Usefulness of the sum absolute QRST integral to predict outcomes in patients receiving cardiac resynchronization therapy. J Cardiovasc Electrophysiol 118(3):389–395McMurray JJ (2010) Clinical practice. Systolic heart failure. N Engl J Med 3623:228–238Meyer CR, Keiser HN (1977) Electrocardiogram baseline noise estimation and removal using cubic splines and state-space computation techniques. Comput Biomed Res 10:459–470Ortigosa N, Giménez VM (2014) Raw data extraction from electrocardiograms with portable document format. Comput Meth Programs Biomed 113(1):284–289Ortigosa N, Osca J, Jiménez R, Rodríguez Y, Fernández C, Galbis A (2016) Predictive analysis of cardiac resynchronization therapy response by means of the ECG. 2016 Comput Cardio 43:753–756. https://doi.org/10.22489/CinC.2016.218-415Ponikowski P, Voors AA, Anker S, Bueno H, Cleland JG, Coats AJ et al (2016) 2016 ESC guidelines for the diagnosis and treatment of acute and chronic heart failure: the task force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur J Heart Fail 18(8):891–975Rad MM, Wijntjens GW, Engels EB, Blaauw Y, Luermans JG et al (2016) Vectorcardiographic QRS area identifies delayed left ventricular lateral wall activation determined by electroanatomic mapping in candidates for cardiac resynchronization therapy. Heart Rhythm 13(1):217–225Shanks M, Delgado V, Bax JJ (2016) Cardiac resynchronization therapy in non-ischemic cardiomyopathy. Journal of Atrial Fibrillation 8(5):47–52Singh JP, Fan D, Heist EK, Alabiad CR, Taub C et al (2006) Left ventricular lead electrical delay predicts response to cardiac resynchronization therapy. Heart Rhythm 3(11):1285–1292Sohaib SM, Finegold JA, Nijjer SS, Hossain R, Linde C et al (2015) Opportunity to increase life span in narrow QRS cardiac resynchronization therapy recipients by deactivating ventricular pacing: evidence from randomized controlled trials. JACC Heart Fail 3:327–336Stockwell RG, Mansinha L, Lowe RP (1996) Localization of the complex spectrum: the S transform. IEEE Trans Signal Process 44(4):998–1001Tang ASL, Wells GA, Talajic M, Arnold MO, Sheldon R et al (2010) Cardiac-resynchronization therapy for mild-to-moderate heart failure. N Engl J Med 363:2385–2395Tereshchenko LG, Cheng A, Park J, Wold N, Meyer TE, Gold MR et al (2015) Novel measure of electrical dyssynchrony predicts response in cardiac resynchronization therapy: results from the SMART-AV trial. Heart Rhythm 12(2):2402–2410van Deursen CJ, Vernooy K, Dudink E, Bergfeldt L, Crijns HJ et al (2015) Vectorcardiographic QRS area as a novel predictor of response to cardiac resynchronization therapy. J Electrocardiol 48(1):45–52Wang TJ (2003) Natural history of asymptomatic left ventricular systolic dysfunction in the community. Circulation 108:977–982Woods B, Hawkins N, Mealing S, Sutton A, Abraham WT et al (2015) Individual patient data network meta-analysis of mortality effects of implantable cardiac devices. Heart 101:1800–1806Ypenburg C, van Bommel RJ, Borleffs CJ, Bleeker GB, Boersma E et al (2009) Long-term prognosis after cardiac resynchronization therapy is related to the extent of left ventricular reverse remodeling at midterm follow-up. J Am Coll Cardiol 53(6):483–490Yu CM, Hayes DL (2013) Cardiac resynchronization therapy: state of the art 2013. Eur Heart J 34:1396–140

A new vicious cycle involving glutamate excitotoxicity, oxidative stress and mitochondrial dynamics

Glutamate excitotoxicity leads to fragmented mitochondria in neurodegenerative diseases, mediated by nitric oxide and S-nitrosylation of dynamin-related protein 1, a mitochondrial outer membrane fission protein. Optic atrophy gene 1 (OPA1) is an inner membrane protein important for mitochondrial fusion. Autosomal dominant optic atrophy (ADOA), caused by mutations in OPA1, is a neurodegenerative disease affecting mainly retinal ganglion cells (RGCs). Here, we showed that OPA1 deficiency in an ADOA model influences N-methyl-D-aspartate (NMDA) receptor expression, which is involved in glutamate excitotoxicity and oxidative stress. Opa1enu/+ mice show a slow progressive loss of RGCs, activation of astroglia and microglia, and pronounced mitochondrial fission in optic nerve heads as found by electron tomography. Expression of NMDA receptors (NR1, 2A, and 2B) in the retina of Opa1enu/+ mice was significantly increased as determined by western blot and immunohistochemistry. Superoxide dismutase 2 (SOD2) expression was significantly decreased, the apoptotic pathway was activated as Bax was increased, and phosphorylated Bad and BcL-xL were decreased. Our results conclusively demonstrate that not only glutamate excitotoxicity and/or oxidative stress alters mitochondrial fission/fusion, but that an imbalance in mitochondrial fission/fusion in turn leads to NMDA receptor upregulation and oxidative stress. Therefore, we propose a new vicious cycle involved in neurodegeneration that includes glutamate excitotoxicity, oxidative stress, and mitochondrial dynamics

Properties and expression of Na+/K+-ATPase α-subunit isoforms in the brain of the swamp eel, Monopterus albus, which has unusually high brain ammonia tolerance

10.1371/journal.pone.0084298PLoS ONE812-POLN

Heart Rate Variability Dynamics for the Prognosis of Cardiovascular Risk

Statistical, spectral, multi-resolution and non-linear methods were applied to heart rate variability (HRV) series linked with classification schemes for the prognosis of cardiovascular risk. A total of 90 HRV records were analyzed: 45 from healthy subjects and 45 from cardiovascular risk patients. A total of 52 features from all the analysis methods were evaluated using standard two-sample Kolmogorov-Smirnov test (KS-test). The results of the statistical procedure provided input to multi-layer perceptron (MLP) neural networks, radial basis function (RBF) neural networks and support vector machines (SVM) for data classification. These schemes showed high performances with both training and test sets and many combinations of features (with a maximum accuracy of 96.67%). Additionally, there was a strong consideration for breathing frequency as a relevant feature in the HRV analysis

Heart Rate Variability Dynamics for the Prognosis of Cardiovascular Risk

Statistical, spectral, multi-resolution and non-linear methods were applied to heart rate variability (HRV) series linked with classification schemes for the prognosis of cardiovascular risk. A total of 90 HRV records were analyzed: 45 from healthy subjects and 45 from cardiovascular risk patients. A total of 52 features from all the analysis methods were evaluated using standard two-sample Kolmogorov-Smirnov test (KS-test). The results of the statistical procedure provided input to multi-layer perceptron (MLP) neural networks, radial basis function (RBF) neural networks and support vector machines (SVM) for data classification. These schemes showed high performances with both training and test sets and many combinations of features (with a maximum accuracy of 96.67%). Additionally, there was a strong consideration for breathing frequency as a relevant feature in the HRV analysis

The nature and extent of evidence on methodologies for monitoring and evaluating marine spatial management measures in the UK and similar coastal waters : a systematic map

Background: Anthropogenic degradation of marine ecosystems is widely accepted as a major social-ecological problem. The growing urgency to manage marine ecosystems more effectively has led to increasing application of spatial management measures (marine protected areas [MPAs], sectoral [e.g. fishery] closures and marine spatial planning [marine plans]). Understanding the methodologies used to evaluate the effectiveness of these measures against social, economic, and ecological outcomes is key for designing effective monitoring and evaluation programmes. Methods: We used a pre-defined and tested search string focusing on intervention and outcome terms to search for relevant studies across four bibliographic databases, Google Scholar, 39 organisational websites, and one specialist data repository. Searches were conducted in English and restricted to the period 2009 to 2019 to align with current UK marine policy contexts. Relevant studies were restricted to UK-relevant coastal countries, as identified by key stakeholders. Search results were screened for relevance against pre-defined eligibility criteria first at title and abstract level, and then at full text. Articles assessed as not relevant at full text were recorded with reasons for exclusion. Two systematic map databases of meta-data and coded data from relevant primary and secondary studies, respectively, were produced. Review findings: Over 19,500 search results were identified, resulting in 391 relevant primary articles, 33 secondary articles and 49 tertiary reviews. Relevant primary articles evaluated spatial management measures across a total of 22 social, economic and ecological outcomes; only 2.8% considered all three disciplines, with most focused exclusively on ecological (67.8%) or social (13.3%) evaluations. Secondary articles predominately focused on ecological evaluations (75.8%). The majority of the primary and secondary evidence base aimed to evaluate the effectiveness of MPAs (85.7% and 90.9% respectively), followed by fisheries closures (12.5%; 3.0%) with only 1.8% of primary, and 6.1% of secondary, articles focused on marine plans or on MPAs and fisheries closures combined. Most evaluations reported within primary articles were conducted for a single site (60.4%) or multiple individual sites (32.5%), with few evaluating networks of sites (6.9%). Secondary articles mostly evaluated multiple individual sites (93.9%). Most (70.3%) primary articles conducted principal evaluations, i.e. basic description of effects; 29.4% explored causation; and 0.3% undertook benefit evaluations. Secondary articles predominately explored causation (66.7%) with the remainder conducting principal evaluations. Australia (27.4%), the USA (18.4%) and the UK (11.3%) were most frequently studied by primary articles, with secondary articles reporting mostly global (66.7%) or European (18.2%) syntheses. Conclusions: The systematic map reveals substantial bodies of evidence relating to methods of evaluating MPAs against ecological outcomes. However, key knowledge gaps include evaluation across social and economic outcomes and of overall merit and/or worth (benefit evaluation), as well as of: marine plans; networks of sites; real-time, temporary or seasonal closures; spatial management within offshore waters, and lagoon or estuary environments. Although the evidence base has grown over the past two decades, information to develop comprehensive evaluation frameworks remains insufficient. Greater understanding on how to evaluate the effectiveness of spatial management measures is required to support improved management of global ocean resources and spaces

Plasma Cholesterol-Induced Lesion Networks Activated before Regression of Early, Mature, and Advanced Atherosclerosis

Plasma cholesterol lowering (PCL) slows and sometimes prevents progression of atherosclerosis and may even lead to regression. Little is known about how molecular processes in the atherosclerotic arterial wall respond to PCL and modify responses to atherosclerosis regression. We studied atherosclerosis regression and global gene expression responses to PCL (>= 80%) and to atherosclerosis regression itself in early, mature, and advanced lesions. In atherosclerotic aortic wall from Ldlr(-/-)Apob(100/100)Mttp(flox/flox)Mx1-Cre mice, atherosclerosis regressed after PCL regardless of lesion stage. However, near-complete regression was observed only in mice with early lesions; mice with mature and advanced lesions were left with regression-resistant, relatively unstable plaque remnants. Atherosclerosis genes responding to PCL before regression, unlike those responding to the regression itself, were enriched in inherited risk for coronary artery disease and myocardial infarction, indicating causality. Inference of transcription factor (TF) regulatory networks of these PCL-responsive gene sets revealed largely different networks in early, mature, and advanced lesions. In early lesions, PPARG was identified as a specific master regulator of the PCL-responsive atherosclerosis TF-regulatory network, whereas in mature and advanced lesions, the specific master regulators were MLL5 and SRSF10/XRN2, respectively. In a THP-1 foam cell model of atherosclerosis regression, siRNA targeting of these master regulators activated the time-point-specific TF-regulatory networks and altered the accumulation of cholesterol esters. We conclude that PCL leads to complete atherosclerosis regression only in mice with early lesions. Identified master regulators and related PCL-responsive TF-regulatory networks will be interesting targets to enhance PCL-mediated regression of mature and advanced atherosclerotic lesions. Author Summary The main underlying cause of heart attacks and strokes is atherosclerosis. One strategy to prevent these often deadly clinical events is therefore either to slow atherosclerosis progression or better, induce regression of atherosclerotic plaques making them more stable. Plasma cholesterol lowering (PCL) is the most efficient way to induce atherosclerosis regression but sometimes fails to do so. In our study, we used a mouse model with elevated LDL cholesterol levels, similar to humans who develop early atherosclerosis, and a genetic switch to lower plasma cholesterol at any time during atherosclerosis progression. In this model, we examined atherosclerosis gene expression and regression in response to PCL at three different stages of atherosclerosis progression. PCL led to complete regression in mice with early lesions but was incomplete in mice with mature and advanced lesions, indicating that early prevention with PCL in individuals with increased risk for heart attack or stroke would be particularly useful. In addition, by inferring PCL-responsive gene networks in early, mature and advanced atherosclerotic lesions, we identified key drivers specific for regression of early (PPARG), mature (MLL5) and advanced (SRSF10/XRN2) atherosclerosis. These key drivers should be interesting therapeutic targets to enhance PCL-mediated regression of atherosclerosis